EP1788523B1 - Correction des signaux lumineux indesirables dans une région d'intérêt spécifique d'une image - Google Patents

Correction des signaux lumineux indesirables dans une région d'intérêt spécifique d'une image Download PDF

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Publication number
EP1788523B1
EP1788523B1 EP06124151.9A EP06124151A EP1788523B1 EP 1788523 B1 EP1788523 B1 EP 1788523B1 EP 06124151 A EP06124151 A EP 06124151A EP 1788523 B1 EP1788523 B1 EP 1788523B1
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EP
European Patent Office
Prior art keywords
correction
interest
regions
region
reaction
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Not-in-force
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EP06124151.9A
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German (de)
English (en)
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EP1788523A1 (fr
EP1788523B8 (fr
Inventor
James C. Kolterman
Eric B. Shain
Robert C. Gray
Shihai Huang
Gavin A. Cloherty
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Abbott Molecular Inc
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Abbott Laboratories
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Priority to EP15161939.2A priority Critical patent/EP2947624A1/fr
Publication of EP1788523A1 publication Critical patent/EP1788523A1/fr
Application granted granted Critical
Publication of EP1788523B1 publication Critical patent/EP1788523B1/fr
Publication of EP1788523B8 publication Critical patent/EP1788523B8/fr
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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30072—Microarray; Biochip, DNA array; Well plate

Definitions

  • This invention relates to a method for correcting signals detected by a detection system in a diagnostic instrument.
  • Cross-talk refers to the situation where a signal from a given location in the image (for example, a given well in a plate having a plurality of wells, e.g., a 96-well PCR plate), causes a variation in the signal at a different location in the image (for example, a different well in the plate having a plurality of wells).
  • a specific region within an image associated with an independent signal is often referred to as a region of interest (alternatively referred to herein as ROI).
  • Each ROI defines the specific pixels within the image associated with a specific reaction. Variations in signal due to cross-talk, although typically small, can induce variations in reaction quantification of one or more regions of interest within the image. In some cases, sensitivity of the reaction is reduced by requiring an increase in signal threshold in order to avoid false positive results due to cross-talk.
  • the areas in the image between the regions of interest of the image contain optical information that can be used to compensate for sources of variation in signal.
  • These sources of signal variation can result from a specific geometric optical reflection, scattered light from optical components, light leakage, changes in intensity of the source of light, and the like. All of these sources of variation can contribute to a dynamically changing error in the optical signal in a given region of interest of the image.
  • YANG Y H ET AL "Analysis of cDNA microarray images" BRIEFINGS IN BIOINFORMATICS, HENRY STEWART PUBLICATIONS, LONDON, GB, vol. 2, no. 4, December 2001 (2001-12), pages 341-349, XP002335348 ISSN: 1467-5463 discloses an image analysis of cDNA microarrays and, in particular, for correcting a spot's measured intensity which includes contributions not due to probe hybridization.
  • the invention provides a method for correcting the signal in an image having a plurality of regions of interest as set out in the appended claims.
  • region of interest means the collection of pixels within an image that define the location of a specific optical signal.
  • reaction region of interest means the region of interest associated with a specific reaction in an assay.
  • region of correction and “correction region of interest” mean the area associated with the background portion of the image adjacent to a reaction region of interest.
  • reaction pixel sum means the sum of all the pixel intensity values within a reaction region of interest.
  • reaction pixel count means the number of pixels within a reaction region of interest.
  • reaction region of interest pixel average means the value obtained by dividing the reaction pixel sum by the reaction pixel count.
  • correction pixel sum means the sum of all the pixel intensity values within a region of correction.
  • correction pixel count means the number of pixels with a region of correction.
  • region of correction pixel average means the value obtained by dividing the correction pixel sum by the correction pixel count.
  • scale means a multiplicative factor applied to the correction calculation.
  • centroid means the geometric center of a region of interest.
  • this invention provides a method for correcting an image having a plurality of reaction regions of interest and a plurality of regions of correction, the method involving the steps of:
  • the centroid of each reaction region of interest is determined.
  • the reaction regions of interest are typically determined by using a calibration where signals in a device having a plurality of reaction sites are measured. A signal is measured at each reaction site.
  • the signals in a calibration plate containing fluorescent dye at each reaction site can be measured by an imaging sensor.
  • a calibration plate is a 96-well reaction plate used for calibrating the instrument used.
  • the reaction regions of interest can be determined by locating the contiguous pixels at each reaction site within the image.
  • the geometric centroid of each set of centroids from four adjacent reaction regions of interest can be used to determine a center point for a region of correction. A region of correction using that center point and a specific geometric shape can be defined.
  • the reaction regions of interest are circular in shape.
  • a region of correction can be circular-shaped, as shown in FIG. 2A , rectangular-shaped, as shown in FIG. 2B , or diamond-shaped, as shown in FIG. 2C .
  • Other shapes such as, for example, closed polygons, are suitable for both the reaction regions of interest and the regions of correction.
  • the parameters of the regions of correction are typically radii of rings for circular-shaped regions of correction, length and width for rectangular-shaped regions of correction, and length of sides for diamond-shaped regions of correction. Dimensions for the particular geometric shape selected are specified.
  • An alternative to defining regions of correction by means of geometric shapes involves the use of an arbitrary bitmap.
  • Such a bitmap could, for example, be a 9 by 9 array of values specifying which pixels would be included in the region of correction and which pixels would be excluded from the region of correction.
  • the center points of the regions of correction can be mirrored to create regions of correction on the periphery of the plate for the outer rows and columns of the reaction regions of interest in the image.
  • the use of diamond-shaped regions of correction is shown in FIG. 2C .
  • the regions of interest associated with specific wells can be determined and stored, such as, for example, by means of a computer.
  • each reaction region of interest has the four adjacent regions of correction associated with it.
  • the rectangles can be oriented with the length parallel to the x-axis or to the y-axis, as shown in FIG. 2B .
  • the center point between two adjacent regions of interest is located.
  • a rectangle is constructed by using the center point between two adjacent regions of interest as the center of the region of correction between the regions of interest.
  • the center point between two adjacent regions of interest is located.
  • the rectangle is constructed by using the center point between two adjacent regions of interest as the center of the region of correction between the regions of interest.
  • Rectangles are also created on the periphery of the image for the outer rows of regions of interest and outer columns of regions of interest.
  • the mirror of the center between adjacent regions of interest is used to set the center of the region of correction rectangle.
  • the regions of interest associated with specific wells can be determined and stored.
  • each reaction region of interest has the four adjacent regions of correction associated with it. Measures other than the centroid of the regions of correction can also be used to define the location of regions of correction. For example, the region of correction can be placed equidistant from boundaries of adjacent regions of interest.
  • a background offset value needs to be generated. This value can be generated in at least two ways.
  • a background calibration can be performed. In this method, an image is taken of a plate without any fluorescent dye.
  • the average pixel value for each region of correction is calculated by dividing the pixel sum by the pixel count in that region of correction to obtain an average pixel value. This average pixel value is indicative of the background light level and is referred to as the background offset value.
  • the background offset values are stored for use in future runs, e.g., PCR runs.
  • the background offset value can be determined on a run-by-run basis by calculating the average pixel value for each region of correction for the first reading of a run, e.g., a PCR run. Because the first (or first few) readings of a PCR run occur before a significant reaction signal is produced, this alternative method provides a good representation of the background.
  • the signal correction is performed in the following manner. Performance of signal correction is depicted in FIGS. 1 and 3 .
  • the reaction pixel sum and the reaction pixel count are calculated by using the reaction region of interest.
  • the average pixel value for the four regions of correction associated with a given reaction region of interest is calculated.
  • four regions of correction are shown in FIG. 1 and diamond-shaped regions of correction are shown in FIG. 1
  • the method is not limited to four regions of correction nor is the invention limited to diamond-shaped regions of correction.
  • the background offset value is subtracted from the region of correction pixel average. Then, this difference is multiplied by the reaction region of interest pixel count and, if necessary, by a scale factor, to generate a correction value.
  • the correction value is then subtracted from the reaction region of interest pixel sum to generate a corrected reaction region of interest pixel sum.
  • the scale factor is typically dependent upon the detection system. An example of a scale factor is 1.15. In some instrument systems, multiple exposures are made at each reading to increase the dynamic range of measurement. In this case, a corresponding background offset and region of correction pixel average needs to be generated for each exposure. The correction to the reaction pixel sum is then made for the exposure of longest duration that does not exhibit significant saturation of the image sensor.
  • This invention can also be applied to an assay system based on array or a microarray, such as, for example, the Vysis GenoSensor genomic DNA microarray system (Abbott Laboratories, Abbott Park, IL).
  • a microarray such as, for example, the Vysis GenoSensor genomic DNA microarray system (Abbott Laboratories, Abbott Park, IL).
  • Such systems can measure a plurality of genomic targets through hybridization to an array of capture targets placed on a surface, such as, for example, a glass "chip” or a microscope slide.
  • the product of the hybridization is typically measured by means of fluorescent dyes and an electronic imaging system.
  • a real time PCR run for HIV was performed on an ABI Prism 7500 instrument (Applied Biosystems, Foster City, CA). This instrument utilizes a 96-well plate format with wells arranged in a 12 x 8 array. The run was configured so that there were 84 wells containing positive samples with a concentration of 1x10 6 copies/mL and 12 wells not containing positive samples, i.e., negative wells. The negative wells were distributed on the plate to maximize the potential cross-talk from the wells containing positive samples.
  • FIG. 4 illustrates the layout of the plate.
  • the ABI Prism 7500 instrument uses a CCD camera and measures fluorescence in five wavelength bands.
  • FIG. 5 shows one image from the end of the PCR run.
  • FIG. 6 shows the same image with the reaction regions of interest and the regions of correction superimposed. In this example, a diagonal array of diamond-shaped regions of correction, each of which contained of 25 pixels, were used.
  • the first reading in the PCR run was used to establish the background offset values for each subsequent reading.
  • the scaling factor used was 1.15.
  • FIG. 7 shows the raw fluorescence signals for all 96 samples without any image-based correction applied.
  • the 84 positive samples generated signals significantly above the background fluorescence by cycle 15 and approached their maximum fluorescence by cycle 25.
  • FIG. 8 shows the same responses with the Y-axis scaled to focus on the responses in wells not containing positive samples. All of the negative responses showed a small but significant rise from cycles 15 through 25, which is caused by cross-talk from the responses of the positive samples.
  • FIG. 9 shows the effect of the image-based correction on the negative responses. As can be seen, the cross-talk signal has been effectively eliminated.
  • FIG. 10 shows the response for well F-11 with and without the image-based correction applied.
  • the method is also applicable to images that contain a fewer or a greater number of regions of interest.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Molecular Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Biotechnology (AREA)
  • Evolutionary Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Genetics & Genomics (AREA)
  • Biophysics (AREA)
  • Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
  • Investigating Or Analysing Materials By The Use Of Chemical Reactions (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)

Claims (14)

  1. Procédé de correction du signal dans une image comprenant un signal variable de manière dynamique et présentant une pluralité de régions d'intérêt, le procédé comprenant les étapes ci-dessous consistant à :
    (a) fournir une image présentant une pluralité de régions d'intérêt, ces régions d'intérêt présentant chacune un signal variable de manière dynamique et des zones entre elles ;
    (b) déterminer une région de correction entre au moins deux régions d'intérêt ;
    (c) calculer un signal de correction à partir de la région de correction ; et
    (d) utiliser le signal de correction en vue de corriger une mesure de signal à partir d'une ou plusieurs régions d'intérêt, caractérisé en ce que l'étape (c) comprend en outre les étapes ci-dessous consistant à :
    (e) déterminer un comptage de pixels de réaction et une somme de pixels de réaction pour chaque région d'intérêt de réaction ;
    (f) déterminer une valeur moyenne de pixel pour au moins une région de correction pour chaque région d'intérêt de réaction ;
    (g) déterminer une valeur de décalage de fond pour chaque valeur moyenne de pixel au niveau d'une région de correction ;
    (h) déterminer une moyenne de pixel et soustraire la valeur de décalage de fond de la moyenne de pixel en vue de produire une valeur de différence de régions de correction pour chaque région de correction ;
    (i) déterminer un signal de correction en multipliant la valeur de différence de régions de correction par le comptage de pixels de régions d'intérêt pour chaque région d'intérêt de réaction ;
    (j) déterminer une somme corrigée de régions d'intérêt de réaction, en soustrayant la valeur de correction de la somme de pixels de régions d'intérêt de réaction pour chaque région d'intérêt de réaction.
  2. Procédé selon la revendication 1, dans lequel le signal de fond correspond à une valeur de décalage de fond stockée avant le début de l'exécution.
  3. Procédé selon la revendication 1, dans lequel le signal de fond correspond à une valeur de décalage de fond déterminée au cours de l'exécution.
  4. Procédé selon la revendication 1, dans lequel le signal de correction est mis à l'échelle.
  5. Procédé selon la revendication 1, dans lequel les régions de correction présentent une pluralité de côtés.
  6. Procédé selon la revendication 1, dans lequel les régions de correction présentent quatre côtés.
  7. Procédé selon la revendication 1, dans lequel les régions de correction correspondent à des polygones fermés.
  8. Procédé selon la revendication 1, dans lequel les réglons de correction sont circulaires.
  9. Procédé selon la revendication 1, dans lequel les régions de correction sont annulaires.
  10. Procédé selon la revendication 1, dans lequel les réglons de correction sont définies par une topogramme binaire.
  11. Procédé selon la revendication 1, dans lequel ladite pluralité de régions d'intérêt provient d'une plaque à puits multiples.
  12. Procédé selon la revendication 1, dans lequel un lecteur de thermocycleur est employé.
  13. Procédé selon la revendication 1, incluant en outre l'étape consistant à stocker les régions de correction définies à l'étape (c).
  14. Procédé selon la revendication 1, dans lequel la somme corrigée de régions d'intérêt de réaction est déterminée pour chaque exposition utilisée en vue de générer l'image.
EP20060124151 2005-11-18 2006-11-15 Correction des signaux lumineux indesirables dans une région d'intérêt spécifique d'une image Not-in-force EP1788523B8 (fr)

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EP15161939.2A EP2947624A1 (fr) 2005-11-18 2006-11-15 Correction basée sur image pour des signaux lumineux indésirables dans une région d'intérêt spécifique

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US11/283,365 US20070116376A1 (en) 2005-11-18 2005-11-18 Image based correction for unwanted light signals in a specific region of interest

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EP15161939.2A Division-Into EP2947624A1 (fr) 2005-11-18 2006-11-15 Correction basée sur image pour des signaux lumineux indésirables dans une région d'intérêt spécifique
EP15161939.2A Division EP2947624A1 (fr) 2005-11-18 2006-11-15 Correction basée sur image pour des signaux lumineux indésirables dans une région d'intérêt spécifique

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ES2537109T3 (es) 2015-06-02
US8249381B2 (en) 2012-08-21
EP1788523A1 (fr) 2007-05-23
EP1788523B8 (fr) 2015-05-06
EP2947624A1 (fr) 2015-11-25
US20070116376A1 (en) 2007-05-24
US20100142848A1 (en) 2010-06-10

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